Urologists
In short: today's best AI models could do about 29% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 71% of the time, stays with people.
Diagnose, treat, and help prevent benign and malignant medical and surgical disorders of the genitourinary system and the renal glands.
$265,930 a year (for the broader BLS group this job sits in).
Reviewed on October 18, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on0 h
- A person checks AI's work12 h
- Desk work AI can't do yet0 h
- Stays with people28 h
Urologists, now: of a 40-hour week, AI could take on 0 hours, 12 hours become checking its work, 0 hours are desk work it can't do yet, and 28 hours stay with people.
The largest pieces: Document patient histories (about 3 h, a person checks); Order and read tests (about 3 h, a person checks); Diagnose and treat urologic disease (about 1 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 14%
- 15%
- 3%
- 14%
- 53%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 29% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 3%. With Claude Mythos Preview (early), measured in April 2026, 29%. Today's estimate: 29%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 14 tasks showed up. Within each of Anthropic's methods, never across a change: none to 0.0027% (released February and March 2025).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | none | n/a | 0 of 14 |
| Released March 2025 | 0.0027% | 634 of 703 | 1 of 14 |
| The week of Aug 4, 2025 (released September 2025) | none | n/a | 0 of 14 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 14 |
| The week of Feb 5, 2026 (released March 2026) | none | n/a | 0 of 14 |
| April 2026 (released June 2026) | none | n/a | 0 of 14 |
| May 2026 (released June 2026) | none | n/a | 0 of 14 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 56% of this job's working time as physical work. For 0% of the working time, a robot has been shown doing most of the task somewhere. 0.00 of 3.
- Not physical 44%
- No robot shown 56%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
70% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Diagnose and treat urologic disease, the hands-on work, 15%
- Treat with urologic instruments, the hands-on work, 12%
- Perform minimally invasive treatments, the hands-on work, 11%
- Perform surgery, the hands-on work, 11%
- Direct the care team, the in-person work, 5%
- Examine with imaging equipment, the hands-on work, 5%
What becomes checking the machine
29% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it.
- Document patient histories, severe if wrong, 7%
- Order and read tests, a licensed person signs, 7%
- Diagnose and treat urologic disease, a licensed person signs, 4%
- Prescribe medications, a licensed person signs, 4%
- Prescribe or give infection treatment, a licensed person signs, 3%
- Advise other clinicians, a licensed person signs, 1%
What to learn
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
- Signing off under your license. Some tasks need a licensed, certified or sworn person to do or sign them. The license, and the judgment it stands for, stays with the person.
- The hands-on craft. About 53% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check or sign: spotting what a draft gets wrong is a skill of its own.
- Handling protected records. Much of the work touches protected personal records: knowing what may be shared with a model, and how, is part of the job.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 14 tasks from .
| Task | ||||
|---|---|---|---|---|
| Diagnose or treat diseases or disorders of genitourinary organs and tracts including erectile dysfunction (ED), infertility, incontinence, bladder cancer, prostate cancer, urethral stones, or premature ejaculation.Examining and treating the patient, with the record.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 18% | 50 min25 min to 1.7 h | Hands-on 50%, in person 30%, documents 20% | 20%Desk part half by now |
| Treat lower urinary tract dysfunctions using equipment such as diathermy machines, catheters, cystoscopes, or radium emanation tubes.Procedures done by hand with scopes and catheters.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 12% | 50 min25 min to 1.7 h | Hands-on 100% | Stays with people |
| Treat urologic disorders using alternatives to traditional surgery such as extracorporeal shock wave lithotripsy, laparoscopy, or laser techniques.Lithotripsy, laparoscopic and laser procedures done by hand.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 11% | 1.7 h50 min to 3.3 h | Hands-on 100% | Stays with people |
| Perform abdominal, pelvic, or retroperitoneal surgeries.Operating in the theater.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 11% | 3.3 h1.7 h to 6.7 h | Hands-on 100% | Stays with people |
| Document or review patients' histories.The history written and reviewed in the record.Done hourly or more by most who do it. AI observed on this task. | 7% | 17 min8 min to 33 min | Systems 100% | 100%Half by now |
| Order and interpret the results of diagnostic tests, such as prostate specific antigen (PSA) screening, to detect prostate cancer.Orders entered and results read in the record.Done daily by most who do it. | 7% | 17 min8 min to 38 min | Documents 60%, systems 40% | 100%Half by now |
| Direct the work of nurses, residents, or other staff to provide patient care.Directing nurses and residents on the ward and in the clinic, with orders written.Done daily by most who do it. | 6% | 25 min13 min to 50 min | In person 80%, documents 20% | 20%Desk part half by now |
| Examine patients using equipment, such as radiograph (x-ray) machines or fluoroscopes, to determine the nature and extent of disorder or injury.Running the imaging at the machine and reading what it shows.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 6% | 25 min13 min to 50 min | Hands-on 80%, documents 20% | 20%Desk part half by now |
| Teach or train medical and clinical staff.Teaching on the ward and in the clinic, with some written material.Done daily by most who do it. | 5% | 50 min25 min to 1.7 h | In person 80%, documents 20% | 20%Desk part half by now |
| Perform brachytherapy, cryotherapy, high intensity focused ultrasound (HIFU), or photodynamic therapy to treat prostate or other cancers.Brachytherapy, cryotherapy and focused ultrasound done by hand.Done yearly or less by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 2.5 h1.3 h to 5 h | Hands-on 100% | Stays with people |
| Prescribe or administer antibiotics, antiseptics, or compresses to treat infection or injury.The prescription entered, or the treatment applied by hand.Done daily by most who do it. | 4% | 17 min8 min to 33 min | Systems 40%, hands-on 40%, documents 20% | 60%Desk part half by now |
| Provide urology consultation to physicians or other health care professionals.Consultations with other physicians by call or note.Done daily by most who do it. | 4% | 25 min13 min to 50 min | Conversation 70%, documents 30% | 30%Desk part half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
Where this job works
The industry groups that employ the most of it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Questions about this job
- How much of the work of Urologists is within reach of AI now?
- An estimated 29% of the working time is within reach of AI models now and 29% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Urologists come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Document patient histories (100% of the task's time now); Order and read tests (100% of the task's time now); and Diagnose and treat urologic disease (20% of the task's time now).
- Which tasks of Urologists stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Treat with urologic instruments; Perform minimally invasive treatments; and Perform surgery. Together such tasks are about 38% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Urologists learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are judgment where errors are severe; signing off under your license; and the hands-on craft. By the end of 2028 on the long-run pace at four in five, about 70% of the working time stays with people, 29% becomes checking a model's work and 0% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Urologists?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 3%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Urologists?
- Anthropic's robot exposure rating (September 2026) finds 56% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 0% of the working time. Its index is 0.00 of 3. A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 14 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on October 18, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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